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Using Python to Implement a Complete Machine Learning Flow

1 hour session (All Time Zones)
Presenter: John Aynsley

Co-Founder and Technical Fellow

Asia and Europe

Time: 10-11am (BST) 11-12pm (CEST) 2.30-3.30pm (IST)

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Americas

Time: 10-11am (PDT) 11-12pm (MDT) 12-1pm (CDT) 1-2pm (EDT)

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Webinar Overview:

In this webinar we will take a fresh look at both Python and Machine Learning.

We will show how to implement, train, and run a simple neural network model, taking advantage of the Keras API used by TensorFlow, because very few people code neural networks from scratch in Python these days. Along the way, we will describe some of the machine learning principles being used, although the focus here is on the coding, not the theory.

The webinar will explore the Python language features needed both to prepare datasets and to code and train neural network models and examine the options available for using Python across the whole machine learning flow, from data gathering and curation through model training to deployment.

In summary, the webinar will cover:

  • How to code up neural network models using Python and Keras
  • How to prepare datasets using Python, Numpy, and Pandas
  • The front-to-back machine learning flow.

At the end of the broadcast we will also feature some related solutions by our webinar partner Toradex. 

John Aynsley

John Aynsley , Doulos Co-Founder and Technical Fellow, will be presenting this training webinar, which will consist of a one-hour session (see below for details) and be interactive with Q&A participation from attendees.

Attendance is free of charge

If you have any queries, please contact webinars@doulos.com

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Related training available from Doulos:

Please contact Doulos to schedule a public course to suit you, or to discuss onsite training.